SOC Performance Technical Lead, Google Cloud

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering, or equivalent practical experience.
• 8 years of experience in SoC or CPU performance and power modeling, analysis, and debugging.
• Experience in programming languages such as C, C++, Python, or Similar.
• Experience in computer architecture, including in areas like interconnects, traffic QoS, distributed caches, and I/O flows.

Preferred Qualifications:

• Experience with hardware description languages like Verilog or SystemVerilog.
• Experience in pre and post-silicon analysis and debugging.
• Experience in productizing features that enhance the performance or power characteristics of a design.
• Experience in building fast, accurate SoC/CPU performance models in C++.
• Experience in one or more functional areas, such as coherent fabrics (e.g., AMBA CHI/AXI), memory controllers (e.g., LPDDR5, DDR5), or I/O controllers (e.g., PCIe, CXL).
• Ability to independently identify, troubleshoot, and solve complex performance problems.

About The Job

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

As a SOC Performance Technical Lead, you will drive the success of our System-on-Chip (SoC) products. You will be focused on ensuring our SoCs deliver maximum performance, power efficiency, and cost-effectiveness. You will be a multi-disciplinary expert who can bridge the gap between deep learning, advanced algorithms, and hardware/software design to create innovative solutions for current and future product lines.

You will lead and oversee a team, setting the technical direction and making critical decisions on frameworks, methodologies, and tools. You will require a collaborative approach with various teams to ensure alignment with organizational goals.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

Responsibilities

• Utilize performance and power models from the architecture team, as well as lab measurements, to validate and tune performance against established goals.
• Exercise open source benchmarks, analyze the results, and find optimization opportunities.
• Develop and implement advanced technologies for running benchmark representations on pre-silicon environments.
• Analyze complex problems, identify core design weaknesses, and drive the resolution of performance issues in both pre and post-silicon environments.
• Develop performance measurement frameworks, including Key Performance Indicators (KPIs), to produce regular reports and dashboards that support stakeholder decision-making.